Study On Algorithm Of Knowledge Acquisition Based On Fuzzy Rough Set

In recent years, data gathered by enterprises increase rapidly because of wide use of information technology, but large volumes of data is not fully used and exploited after being collected, and databases which are full of useful information become data tombs that no body can make use of, which is an enormous waste of resource. The rise and rapid development of technology of knowledge engineering make drawing useful information from large volume data possible.Knowledge acquisition based on rough set has been a very important method. Rough set theory gives knowledge a new definition. Knowledge is a partition of universe and granularity in this theory. People can reduce knowledge and analyze its dependence by this theory.However, it is necessary to discrete the continuous attribute value before reducing knowledge. This porcess may create information lost to a certain degree because discrete value cannot reserve the difference of its real value. Fuzzy set also apply to reach of incomplete, inaccurate problems of knowledge in information systems. Fuzzy set emphasizes the fuzzy nature of set and utilizes the fuzzy nature of knowledge in information systems. In 1992, French scholar D.Dubios and H.Prad presented the definition of fuzzy rough set combined rough set and fuzzy set, solving the problem of information loss in the course of attribute discreted based on rough set.First, the author systematically summarizes current research and tendency of fuzzy rough set theory in this article.Second, the method to fuzzify attributes--fuzzy clustering is researched perticularly, the method to fuzzify composite attributes is presented. In view of the deficiency of attribute fuzzified method, the fuzzy C means clustering is introduced in the article in order to fuzzify the continual attribute, and the best minute class number is obtained by the valid analysis of clustering. Then, the attribute degree of membership matrix which obtained by attribute fuzzified is used to attributes reduction, and an algorithm of attributes reduction based on fuzzy rough sets is given, and the algorithm has a good computing complexity and easy to implement.At last, the full process of knowledge acquisition based on fuzzy rough set is explained by a simple meteorology information system. The result indicates that this method can gain the practical significance but small knowledge collection. Glass...